TING LIU1,2, ZANCAI XIA1,*.
1.School of Tourism, Hunan Normal University, Changsha 410081, China.
2.School of Management, Hunan City University, Yiyang, 413000, China.
Abstract
This study presents a technical assessment framework for accessibility infrastructure in complex topographical conditions, addressing critical engineering challenges in mountainous terrain where elevation gradients exceed 35 degrees. The research examines barrier-free infrastructure performance and construction feasibility through field investigation at Huangshan, integrating Analytic Network Process (ANP)-Delphi methodology with advanced geotechnical analysis. Technical evaluation conducted from March 2023 to February 2024 encompassed systematic GPS mapping, material performance testing under extreme weather conditions, and consultations with 45 construction engineers and 120 accessibility design specialists. The assessment framework comprises three engineering dimensions: structural integrity and foundation stability (weighted 0.45), material durability and weather resistance (0.35), and construction feasibility under terrain constraints (0.20). Analysis reveals critical engineering thresholds across elevation zones, with low-gradient areas (0-15°) permitting conventional construction methods while steep terrain (>30°) necessitates specialized anchoring systems and reinforced foundations, increasing implementation costs by approximately 200%. Geospatial analysis demonstrates pronounced infrastructure concentration patterns, with feasible construction zones achieving 85% implementation rates while areas exceeding 45° gradients maintain only 15% coverage due to prohibitive engineering challenges. Technical assessment confirms strong negative correlation between construction viability and terrain complexity (r = -0.73, P < 0.01), alongside positive correlation between infrastructure quality metrics and structural performance indicators (r = 0.82, P < 0.001). These findings provide quantitative benchmarks for barrier-free infrastructure planning in mountainous tourism destinations with comparable topographical challenges.
Keywords: Accessibility Infrastructure; Complex Topography; Technical Assessment; Construction Engineering; Mountain Terrain; Structural Performance
1.Introduction
Mountains pose significant engineering difficulties in the construction of accessibility infrastructure with extreme topography variation, unstable geology, and harsh weather effects on material performance. The establishment of barrier-free infrastructure in slopes over 30 degrees, as exemplified by Huangshan’s intricate geological formations, requires cutting-edge technical solutions outside traditional construction norms. The network, with more than 3.3 million users each year, has significant demographics that need access features, which elevates the engineering requirements for robust, weather-tight installations. However, the site continues to face significant challenges in providing appropriate access to all visitors. Studies show that tourism is hampered by reduced accessibility for people with disabilities, which represents about 27% of the potential market [1]. This difference underlines why there is an urgent need to better assess and improve the accessibility of mountainous construction sites. Current estimates predict that about 15% of the world’s population will face some form of disability, mainly due to aging and the increasing prevalence of chronic health problems[2]. In particular, China has 85 million people with disabilities and 267 million people over the age of 60, representing 18.7% of the country’s total population [3].
Implementing accessible infrastructure in mountain tourist destinations presents unique challenges, especially in the complex topography of the huangshan mountains. The site includes 77 summits of more than 1000 metres in height connected by steep passages that constitute a major obstacle to changes in accessibility. For the purposes of this study, “accessibility” refers to the comprehensive design and implementation of facilities, information systems and services to ensure equitable access for people with different mobility abilities and sensory or cognitive needs. This concept contains three inseparable dimensions, namely, physical accessibility (building architecture provides easy traffic and use facility), information accessibility (language and communication system make the construction understandable and navigable), and service accessibility (staffs’ assistance and operational hours). In addition, this multi-aspect model extends the conventional infrastructure model to address the complicated accessibility need in the vulnerable setting of mountainous tourism area. At the same time, the huangshan mountains are designated as a World heritage site by UNESCO and have a development plan for ‘tourism for all’ and yet only 45% of tourism facilities in the huangshan mountains meet national accessibility criteria, as measured by local inspectors [4]. The technical difficulties involve a variety of technical contents, such as, various engineering standards of compliance (GB 50763-2012 Code for Accessibility Design), dynamic loading condition requirement for stability, material performance demand under high altitude, especially the requirement of engineered materials possessing the performance index that the freeze-thaw resistance of the material exceeds 100 times, the retention friction co-efficient of the material in a wet state exceeds 0.6, the adaptability of annual water precipitation beyond 2,300mm and the adaptability of temperature variation ranging from -20 ° C to 45 ° C[5].
In China, since the ratification of the United Nations convention on the rights of persons with disabilities in 2008, the concept of disability has changed dramatically, indicating a paradigm shift from the welfare model to the rights model. China’s disability classification system can be divided into seven types of disabilities: visual, hearing, language, physical, mental and multiple disabilities. In 2012, the “barrier-free environment ordinance” established the national comprehensive standards for accessibility-compliant construction systems. However, in mountain resorts like huangshan, there are unique challenges to traditional Chinese values of family care and modern universal design principles. Therefore, a culturally sensitive approach is needed to harmonize international norms with the cultural background of the community.
In a UNESCO world heritage site, the development of sustainable and barrier-free tourism harmonize the three basic requirements of ensuring equitable access for disabled people, protecting the ecological integrity of fragile mountain ecosystems, and protecting the cultural authenticity To be able to do that. It’s a triple challenge. This reflects the complexity inherent in the broad development of a sustainable construction practices industry, and takes into account the macro level of which sites need environmental justice, social inclusion and intergenerational fairness. The improvement of accessibility and the protection of the tension between huangshan mountain represent various trade-offs in the development of natural tourism in the world. Infrastructure changes must take into account not only direct functional efficiency, but also their consistency with the broader sustainable development goals. The integrated framework for sustainable development, including social equity, environmental protection and cultural protection, provides an analytical perspective, especially huangshan, where the decision-making of the infrastructure field has a great impact on long-term resource management.
The complex and multi-use nature of present day accessibility infrastructure necessitates engineered solutions that can support a variety of users and provide longevity to withstand extreme environmental conditions. Technical requirements are also fairly broad: Different loads (ranging from standard pedestrian traffic to specialised mobility equipment), and durability can be affected by constant exposure to humidity, temperature variations and mechanical pressures. The incorporation of such performance requirements in the context of steep areas sets new standards for mountain tourism destinations.
This research addresses critical gaps in the literature by developing and validating a comprehensive evaluation index system for barrier-free infrastructure through an empirical case study of Huangshan Scenic Area. Employing a mixed-methods approach that integrates quantitative metrics and qualitative assessments, this study addresses three primary research objectives:
(1) To analyze engineering solutions for accessibility infrastructure implementation in terrain exceeding 30-degree gradients, addressing foundation stability, material selection, and structural performance under extreme environmental conditions;
(2) To evaluate technical compliance with international accessibility standards (ISO 21542:2011) and Chinese construction codes (GB 50763-2012) within the constraints of heritage site preservation requirements;
(3) To develop evaluation criteria that holistically assess the interrelationships among physical infrastructure, information systems, and maintenance protocols within environmentally sensitive mountain contexts.
Structural performance metrics considered in the engineering appraisal include load carrying capacity estimates, material fatigue test results and slope coefficient of stability. Technical criteria for evaluation include design parameters of foundation, effectiveness of drainage system, and long-term performance expectation under arbitrary cycles of environmental loading. Moreover, the proposed evaluation framework has been actually implemented and validated within Huangshan Scenic Area through field experiments in three typical zones, namely the Eastern Steps region, the Western Steps region, and the Celestial Capital Peak region. This bottom-top approach, which accompanies the theoretical construction, provides peactical contributions to how accessibility and inclusivity can be improved in MRs without damaging their inherent natural and cultural value. The technology requirements and engineering technologies in the Huangshan case are also quantified standards that can be referenced for the accessibility facilities of similar landforms.Finally, the paper has made an effort to build model-based evaluation method to advance the developing stage of the tourism destinations in the mountains.
2. Literature Review
2.1 Technical Framework for Accessibility Infrastructure in Mountain Terrain
The design of technical forms of technical control (assessment and management) of accessibility infrastructure in mountain relief are posed to solve some basic engineering problems, which cannot be solved using conventional construction standards.get dataow, insertedtext 10 getinsNConstructing Standards for Mountain Topography on Gradients over 35° with Differences in Elevation over 1000 Meters as Geodesic Bases for Modern Productionget dataow, insertedtext 102 getinsNstandards for Mountain Topography: On Gradients over 35°, with Differences in Elevation over 1000 Meters, as Geodesic Bases for Modern Production. This research has contributed to advancement in structural engineering methodology that was to systematically integrate geotechnical stability requirements, material performance under extreme weather conditions and conformity with international accessibility standards which includes ISO 21542:2021[6] and GB 50763-2012[7] within environmentally sensitive construction contexts
This study contributes to scholarship on barrier-free mountainous tourism destinations in two ways. First, it creates an integrated assessment model that quantitatively assesses the relationship between accessibility improvement and conservation goals in the mountain areas that goes beyond traditional models which are centred in determining the relationship in city areas, Second, a multidimensional conceptualization framework is presented that integrates physical, informational and technical quality dimensions that is been shaped specifically for the mountain tourism resort environment. The technical requirements demand that accessibility systems in the mountains are designed to withstand higher loads due to gradient-forces, with a safety factor of 2.5 to 3.0 for slopes over 30 degrees according to current engineering codes. Material performance is required to maintain frictional coefficient above 0.6 in wet circumstances for non-skid surfaces, with less than 15% loss in strength after 100 freeze-thaw cycles and corrosion resistance compatible with high cyclic humidity areas with relative humidity is greater than 80%. Roman et al. [8] pioneered the conceptual framework of “adaptive accessibility,” while Lovelock and Lovelock [9] have laid down the ethical grounds to prioritize social inclusion within the sphere of construction.
Modern engineering methods are currently utilized, including integrated design paradigms through the adoption of Building Information Modeling (BIM) for terrain evaluation, the use of advanced geotechnical technologies for optimizing foundations and pre-fabricated modular construction systems that can reduce assembly time by 30-50% on site approximately and provide quality control that is not possible at remote mountain location using traditional construction methods [10]. The key technologies to be further developed are advanced large scale structural design parameter, transport logistics for oversize components and setting up procedures in the face of restricted site access and weather-dependent construction windows. More recently, Qiao et al. [11] developed “smart accessibility” using digital technology, where as Lukoseviciute and Nelson [12] discussed the theoretical concept of “graduated accessibility” for different levels of ability.
2.2. Technical Assessment Methodologies for Accessibility Infrastructure in Mountain Engineering
Accessibility infrastructure technical assessment methodologies in Alpine areas transitioned from simple checks of compliance between laws, norms, regulations and codes to full performance evaluation systems including structural calculations, material tests, but also geotechnical stability evaluations at extreme operative temperature and time conditions. Such development highlights the fact that the engineering community acknowledges infrastructure in mountainous areas is subject to nonstandard combinations of static and dynamic loading, temperature variations of -20 to 45°C, as well as material degradation due to more than 100 cycles of freezing and thawing, all of which necessitate innovative reinforcement techniques for these mountainous highways. State-of-the-art monitoring technologies combine finite element simulation for stress field modelling, non-destructive inspection methods for in-service material state, and real-time health monitoring systems that can identify performance decay prior to reaching a critical failure condition. Engineering assessment philosophy has developed from binary compliance verification to the full assessment of the inherent reliability of the structure under different loadings and environmental conditions and for different states of health of the material[6]. This evolution recognizes that infrastructure behavior spans a continuum that depends on multiple correlating variables such as foundation settlement rates, fatigue properties of materials, and the degradation mechanisms of high altitude environments. The use of evaluation techniques for assessing the probability of degradation of structural elements, allows to establish the limit state according to a threshold of the structural relevance of considered types of elements with respect to the uncertainties related to the material properties, the tolerance construction and the load conditions.
The latest developments in quantitative structural assessment are based on the multi-criteria decision analysis (MCDA) frameworks which can assess the performance of infrastructure across various engineering domains (e.g. structural integrity, material durability, construction in challenging environment, long-term maintenance under severe environmental conditions). Geotechnical analysis software paired with Building Information Modeling (BIM) enhances three-dimensional visualization of below-ground conditions, leading to improved foundation design that incorporates varying rock quality, shifts in groundwater, and the risk of slope instability with gradients in excess of 35 degrees. Such an approach is a radical departure from previous mechanistic examining systems. Modern engineering object evaluation involves a time-dependent reliability estimation which takes into consideration material property degradation, the accumulation of fatigue under cyclic load and time-dependent degradation mechanisms characteristic for the mountainous environment such as carbonation, ingress of chlorides and alkali-silica reaction in the concrete constructions exposed to severe weather conditions. Wireless sensor network and machine learning based dynamic structural health monitoring systems provide the capability of online monitoring of structural performance to realize the detection of anomalies in the structural response for identifying any incipient failure mechanism that would need preventive maintenance intervention.
These methodological developments form the basis for an integrated engineering evaluation process consisting of geotechnical testing procedures for complex terrane situations, advanced material analysis procedures for application to extreme environments, reliability-based analysis procedures for consideration of uncertainties, and life-cycle performance models, accounting for accelerated decay processes, in mountain environments. This synthesis of assessment techniques allows the engineer to develop durable solutions that will retain their performance properties over the intended life of the structure (often 75 to 150 years) despite exposure to harsh environmental extremes such as temper-ature extremes, moisture intrusion, freeze/thawing action, and earthquake forces encountered in mountainous regions. This paradigm shift towards comprehensive assessment methodologies allows for the development of multilevel evaluation schemes that covers the complex reality of mountainous tourism destinations accessibility and at the same time advancing universal design approaches and sustainability goals.
2.3 Material Selection Criteria for Barrier-Free Infrastructure in Extreme Mountain Environments
As Alpine construction environment features elevation difference more than 1000m and temperature variation from -20℃ to 45℃, giving full play to advantage of Alpine infrastructure requires strict materials selection criterion, which are much higher than urban construction traditional specification. State-of-the-art material science applications in the construction of mountain infrastructure show that efficient barrier-free installations can only be achieved with engineered materials with improved durability, such as freeze-thaw incorporating addition to the 100 cycles with less than 15% loss of resistance, friction coefficients steady above 0.6 in the wet condition at temperatures approximating the freezing, corrosion resistance suitable for environment where relative humidity remains above 80% and the precipitation exceeds by far 2,300mm annually. Advanced composites such as fiber reinforced polymer (FRP) composite resins are better suited for mountain terrain with characteristic tensile strength above 600 MPa, and remains flexible in sub-zero condition, is resistance to ultraviolet degradation with less than 5% loss of properties after exposure to 2000 hours, and is self-cleaning with a 40% reduction in maintenance over conventional materials like steel. The blend of nano-enhanced concrete mixes designed for high-altitude uses silica fume at 8.0-12.0% and polymer additives to reduce the viscosity at low temperatures, and provide a compressive strength >60MPa, required in order to support the weight of accessibility equipment on steep slopes where the dynamic forces are 2.5-3 times that at the lower altitude conditions[2].
Sustainable, local material options Two are available in either granite aggregate sourced from the locality or locally sourced granite aggregate combined with high performance binders, proving they are both environmentally-friendly and can achieve high performance values, with slip resistance at above 65 in wet conditions and withstanding the thermal cycling range of 60oC, vital for pathway surfaces exposed to direct solar radiation during the summer and winter freezing temperatures. The use of modular steel systems made with high weather-resistant steel alloys (ASTM A588/A588M) with additional atmospheric corrosion resistance allows eliminating surface protection treatment in high-humidity areas and use of pre-fabrication technologies to shorten on-site construction time by 30-50%, which is critical for environmental preservation under time constraints in environmentally sensitive habitats.
Material selection protocols must integrate life-cycle cost analysis accounting for initial material costs, installation complexity in terrain with limited access requiring helicopter transport for components exceeding 500kg, maintenance requirements under extreme weather exposure, and end-of-life recyclability aligned with sustainability objectives, with empirical data indicating that advanced composite materials despite 40-60% higher initial costs demonstrate superior life-cycle economics through reduced maintenance requirements and extended service life exceeding 50 years compared to 25-30 years for conventional materials in comparable mountain environments[13].
2.4 Engineering Standards and Technical Specifications for Mountain Accessibility Infrastructure
Rationalization conscientious review of practical requirements from engineering standards demonstrates that present building codes and civil engineering specifications are fundamentally deficient when used for mountain environment where sloping exceeds 35 degrees and static and dynamic cyclic environmental loads are borne by structural members. Current design practices, which were mostly developed for urban sites with flat topography and moderate exposure conditions, do not account for the complex engineering conditions presented by variable geology, accelerated freeze-thaw degradation and the need for specialized foundation systems to support both gravity and lateral forces on a slope. Existing design evaluation methods cannot adequately solve the challenging mountain construction problems, e.g., the combination of structural analysis, geotechnical investigation, consideration for material science and constructibility problems as well, and the access to and physical conditions at the construction sites, etc. Currently available structural design software, adjusted to normal loading conditions and traditional foundation solutions, need to be heavily modified in order to properly simulate the soil-structure interaction mechanisms, the progressive failure modes and the time dependent degradation due to mountain infrastructure and environmental exposure. Geotechnical studies show significant differences in bearing capacity, settlement behavior, and slope stability factors between mountainous and urban construction sites, and increase by 50 to 100% in the values of the factor of safety for critical infrastructure in slopes greater than 30° and slope angle greater than slope angle- 30 degrees). These differences require a rethinking of design methodologies, construction sequencing and quality control procedure which leads to guaranteed structural performance at the desired target reliability even though increasing uncertainties in subsoil characteristics, material behavior under severe loading conditions and long-term degradation.
The engineering assessment framework developed through this investigation addresses identified technical deficiencies through integrated methodological approaches incorporating advanced finite element modeling for irregular terrain geometries, probabilistic reliability analysis accounting for parameter uncertainty in mountain environments, specialized material selection criteria for extreme weather resistance, and innovative construction methodologies including modular prefabrication and helicopter-assisted assembly for sites with severely limited access. This comprehensive technical framework establishes quantifiable performance criteria validated through full-scale field testing, laboratory material characterization, and numerical simulation calibrated against monitored infrastructure behavior under actual service conditions in mountain environments. This multidimensional approach establishes a methodologically robust foundation for evaluating barrier-free infrastructure in environmentally sensitive mountain contexts, where conventional urban-centric frameworks prove fundamentally inadequate.
3. Materials and Methods
3.1 Study Area
Situated in the southern part of Anhui Province, Huangshan Scenic Area is about 400 kilometers (250 miles) away from Shanghai, listed as World Natural and Cultural Heritage in 1990. Covering an total area of 160.6 square kilometres, the system includes 72 peaks over 1,000 meters high, with the tallest peak, Lotus Peak, soaring to an altitude of 1,864 meters. The topography is complicated, and contains steep granite outcrops, cavern and rock steps, and steep slopes (with gradient of 35° on average), all of which pose significant challenges to the construction of accessible facilities in barrier-free.
The region experiences substantial precipitation (2,395 mm annually) coupled with persistently high humidity levels (averaging 80%), conditions that significantly complicate both the construction and maintenance of accessibility infrastructure. These climatic factors, in conjunction with material degradation concerns and stringent conservation mandates, render barrier-free design exceptionally challenging. The site’s distinctive geomorphological and ecological features encompass thermal springs, ancient Pinus specimens, dramatic granite formations, and the atmospheric phenomenon locally termed the “sea of clouds” [14].
Existing accessibility infrastructure comprises 65 kilometers of pedestrian pathways, aerial cable car systems, and various support facilities. However, compliance with national accessibility standards remains limited to 45% of facilities, with particular deficiencies noted in the Eastern Steps, Western Steps, and Cloud Valley Temple sectors [15]. Despite accommodating over 3.5 million annual users, including substantial proportions of elderly individuals and people with disabilities, critical gaps persist in barrier-free infrastructure implementation [16].
The convergence of extreme topographical constraints, adverse climatic conditions, and heritage conservation imperatives necessitates innovative approaches to barrier-free design that simultaneously ensure accessibility and preserve the site’s irreplaceable natural and cultural heritage values.
3.2 Data Collection
This study employed a mixed-methods data collection strategy integrating field surveys, institutional records, and digital sources to comprehensively assess barrier-free infrastructure within Huangshan Scenic Area. From March 2023 to February 2024, systematic ground surveys were conducted across three primary tourist zones: the Eastern Steps, Western Steps, and Cloud Valley Temple sectors. Spatial data acquisition utilized high-precision GPS receivers (Trimble GeoXH 6000, ±0.25m accuracy) to document barrier-free infrastructure locations, with measurement validity ensured through triple-redundancy verification protocols. Spatial analysis was performed using ArcGIS 10.5, employing the Network Analyst extension to evaluate facility distribution patterns and service coverage areas. Multiple GIS analytical techniques were applied to assess spatial accessibility: kernel density estimation examined facility distribution patterns, network-based service area analysis quantified accessibility coverage, and terrain analysis elucidated slope-facility relationships. Environmental parameters including elevation, slope gradient, and aspect orientation were integrated to identify topographical constraints affecting accessibility implementation in mountainous terrain.
All collected data underwent rigorous standardization using min-max normalization following the equation:
where x’ represents the normalized value, and and represent the minimum and maximum values respectively for each indicator. This standardization process ensured comparative analysis capability across different measurement scales and facility types.
Data quality assurance employed iterative validation protocols including GPS coordinate verification through continuous monitoring, cross-referencing of facility attributes with institutional documentation, and systematic error detection using GIS validation tools. The spatial database was enhanced through integration of topographical data (30m resolution DEM) obtained from the Resource and Environment Science Data Centre, enabling comprehensive accessibility analysis that incorporated both terrain characteristics and facility distribution patterns.
Qualitative data collection involved structured consultations with 45 infrastructure engineering professionals and 120 facility users with mobility limitations, examining structural performance requirements, technical compliance with accessibility standards, and operational constraints in mountainous terrain [5]. Complementary quantitative data encompassing environmental and infrastructural parameters were obtained from governmental agencies and authoritative sources detailed in Table 2, subsequently processed within ArcGIS 10.5 for geodatabase construction [17]. Climate-accessibility relationship analysis utilized historical meteorological data spanning 2013-2023 from the Huangshan Meteorological Bureau, while terrain complexity assessment employed 30m resolution digital elevation models sourced from the Resource and Environment Science Data Centre [18].
The structured consultations with engineering professionals and facility users with mobility limitations (n=165) incorporated technical assessments addressing load-bearing requirements for assistive equipment, surface friction coefficients under varying weather conditions, and structural durability specifications for high-traffic accessibility infrastructure. Standardized assessment protocols examined the engineering parameters governing barrier-free infrastructure design in extreme environmental conditions, facilitating identification of critical performance thresholds and failure modes specific to mountain infrastructure applications.
Comprehensive data processing procedures encompassed quality verification, elimination of redundant information, format standardization, and spatial data registration. The consolidated dataset was integrated within a unified geographic information system platform, enabling sophisticated spatial analysis and visualization of barrier-free infrastructure distribution and accessibility patterns throughout the scenic area.
3.3 Research Methods
3.3.1 ANP-Delphi Approach
The evaluation index system was constructed through systematic integration of literature analysis and expert consultation. Preliminary indicators emerged from comprehensive review of existing accessibility criteria, mountainous tourism destinations characteristics, and universal design principles. Indicator selection prioritized three fundamental criteria: representativeness, measurability, and practical applicability within mountainous contexts.
The resulting framework encompasses twenty-seven indicators organized across three primary dimensions: physical accessibility (weighted at 0.45), information accessibility (0.35), and service accessibility (0.20). Physical accessibility received the highest weighting, reflecting empirical evidence that infrastructure constitutes the primary barrier to mountainous tourism destinations accessibility, as demonstrated by its significant negative correlation with structural performance (r = -0.73, P < 0.01).
The ANP-Delphi methodology employed three iterative consultation rounds engaging 25 experts drawn from universities (40%), infrastructure management agencies (35%), and engineering consulting firms (25%). The initial round established the hierarchical structural framework, while subsequent iterations refined dimensional weightings through systematic paired comparisons. High inter-rater reliability (Kendall’s W = 0.82) validated the consensus-based weighting scheme. Notable secondary weightings emerged for facility configuration (0.230) and safety measures (0.231), underscoring their critical importance in mountainous tourism destinations contexts.
The ANP analysis generated a comprehensive supermatrix incorporating all criterion interdependencies, which was subsequently weighted and raised to limiting powers to derive final priority vectors. Integration with Delphi expert validation ensured that the resulting weights balanced theoretical rigor with practical applicability. All consistency ratios remained below the 0.1 threshold, confirming the reliability of expert judgments.
The final hierarchical weighting structure identified infrastructure accessibility as the paramount consideration (0.323), followed by safety measures (0.231) and facility configuration (0.230). This evaluation framework demonstrates robust internal consistency and provides comprehensive coverage of barrier-free infrastructure requirements specific to mountainous tourism destinations environments.
3.3.2 Index System Construction
The evaluation index system was developed through systematic integration of theoretical foundations and empirical assessments of mountainous tourism destinations accessibility. The initial framework synthesized findings from 127 peer-reviewed studies published between 2013 and 2024 that examined barrier-free infrastructure facilities within mountainous tourism destinations contexts. The resulting hierarchical structure comprises three tiers, with three overarching dimensions forming the primary level: physical accessibility, information accessibility, and service accessibility. Each dimension incorporates specialized indicators addressing performance-oriented infrastructure components, including environmental load integration, targeted technical information provision for facility users, and operational systems supporting diverse functional requirements.
Physical accessibility indicators encompass infrastructural elements including rest facility distribution, pathway gradients, surface conditions, and maintenance provisions. These indicators were specifically calibrated for mountain environments, accounting for elevation zones and terrain complexity. The information accessibility dimension evaluates multi-sensory wayfinding systems, emergency communication infrastructure, and navigational support mechanisms. The service accessibility dimension assesses equipment availability, personnel assistance, and emergency response capabilities. The comprehensive framework comprises 27 discrete evaluation criteria distributed across three hierarchical levels, with each primary dimension subdivided into secondary and tertiary components. Indicator selection and refinement adhered to five fundamental criteria: quantifiable measurability, mountainous tourism destinations relevance, accessibility sensitivity, implementation feasibility, and data availability. The complete index system architecture is presented in Table 3.
3.3.3 Evaluation Model
The evaluation model integrates multi-criteria decision analysis with spatial modeling techniques to comprehensively assess barrier-free infrastructure in mountainous regions. This integrated approach employs a three-stage evaluation process encompassing weighted aggregation, spatial analysis, and fuzzy comprehensive evaluation, as illustrated in Figure 3.
The evaluation process commences with data standardization through min-max normalization, transforming all indicators to a uniform comparative scale. The standardized value x’ᵢⱼ for each indicator is calculated as follows:
where represents the original value, and and are the maximum and minimum values respectively.
where represents the weight of indicator i, and is the standardized value of indicator i.
The aspect analysis in Arc GIS 10.5 is conducted by combining data on slope, elevation, facility distribution, and accessibility networks. Buffer analysis is utilised for the assessment of accessibility, and suitability mapping is performed through weighted overlay analysis. As a segregation method, multistage fuzzy comprehensive evaluation is employed to manage the lack of clarity in evaluation criteria. The completed works with the following membership function:
The final evaluation results are classified into five suitability levels, as shown in Table 4. The following sections present the results of applying this evaluation methodology to barrier-free infrastructure in Huangshan Scenic Area.
4. Results
4.1 Construction of Evaluation Index System
The evaluation index system for barrier-free infrastructure in mountainous regions was developed through a systematic two-stage process comprising literature synthesis and expert validation with subsequent weighting. The preliminary indicator set emerged from comprehensive literature analysis examining accessibility criteria, mountainous tourism destinations characteristics, and universal design principles. Indicator selection adhered to three fundamental criteria: representativeness, measurability, and practical applicability within mountainous contexts, as illustrated in Figure 4.
The finalized framework encompasses twenty-seven indicators structured across three primary dimensions: physical accessibility (weighted at 0.45), information accessibility (0.35), and service accessibility (0.20). Physical accessibility received the highest weighting, reflecting its role as the fundamental prerequisite for infrastructure utilization in mountainous regions where structural limitations constitute the primary access barrier. This prioritization is empirically validated by the significant negative correlation observed between physical barriers and operational performance (r = -0.73, P < 0.01).
Drawing upon the ANP-Delphi methodology detailed in Section 3.3.1, the weighting process systematically quantified each indicator’s relative importance within the evaluation framework. Notably, substantial secondary weightings emerged for both facility configuration (0.230) and safety measures (0.231), underscoring their pivotal role in facilitating secure and comfortable navigation across topographically challenging environments. All expert comparison matrices achieved consistency ratios below the 0.1 threshold, validating the statistical reliability of the consensus judgments, as presented in Table 5.
The finalized weighting hierarchy identifies infrastructure accessibility as the paramount consideration (0.323), followed by safety measures (0.231) and facility configuration (0.230). The interconnected nature of these dimensions is evidenced by the significant influence of facility provisions on safety outcomes. This integrated weighting structure establishes a comprehensive evaluation framework that systematically addresses the multifaceted requirements of barrier-free infrastructure in mountainous tourism destinations environments.
4.2 Spatial Analysis of Barrier-free infrastructure
The spatial distribution and coverage of barrier-free infrastructure in Huangshan Scenic Area demonstrate systematic patterns across three interconnected dimensions: infrastructure accessibility, information systems, and service networks. Geographic Information System (GIS) analysis integrated with statistical modeling of 127 barrier-free infrastructure reveals substantial spatial heterogeneity in service distribution throughout the study area. As detailed in Table S1, comprehensive spatial analysis identifies statistically significant clustering patterns in facility distribution (Moran’s I = 0.47, P < 0.01), with service density demonstrating strong negative correlation with terrain complexity (r = -0.73, P < 0.01) and positive correlation with structural performance metrics (r = 0.82, P < 0.001).
Figure 6 presents the spatial distribution of barrier-free infrastructure across Huangshan Scenic Area, revealing distinct clustering patterns that correspond closely with topographical variation. Statistical analysis confirms significant spatial autocorrelation (Moran’s I = 0.47, P < 0.01), indicating systematic rather than random facility distribution across the mountainous terrain. Hot spot analysis identifies statistically significant concentrations of facilities predominantly in the southern, lower-elevation zones characterized by moderate gradients. These high-density clusters coincide strategically with primary circulation routes and service hubs. In contrast, significant cold spots emerge in the central and northern sectors where precipitous terrain poses substantial infrastructure development constraints. This spatial pattern demonstrates the deterministic influence of topographical factors on accessibility infrastructure deployment. Facilities concentrate in areas where terrain characteristics facilitate construction while maintaining adequate user accessibility. Although partial compliance with national accessibility standards has been achieved, considerable spatial gaps remain in topographically challenging areas, underscoring the inherent tension between landscape constraints, accessibility requirements, and infrastructure feasibility in mountainous tourism destinations environments.
Figure 7 illustrates the significant negative correlation between terrain gradient and facility distribution density (r = -0.73, P < 0.01), revealing three distinct topographical thresholds with critical implications for barrier-free infrastructure planning in mountainous environments. Low-gradient zones (0-15°) accommodate optimal facility density, achieving >95% coverage with 8.3 facilities/km². These areas benefit from favorable construction conditions that require minimal engineering modifications. Intermediate-gradient zones (15-45°) exhibit exponential coverage decline from 62% to 38%, corresponding to progressively complex construction requirements and escalating implementation costs. High-gradient zones (>45°) demonstrate markedly limited facility presence, with coverage below 20% and density of merely 0.9 facilities/km². This spatial scarcity results from the convergence of prohibitive construction challenges, safety imperatives, and economic constraints, with development costs exceeding baseline expenditures by approximately 200%.
Statistical analysis identifies 15 degree as the critical inflection point where barrier-free infrastructure implementation transitions from economically feasible to progressively cost-prohibitive. This threshold against which a maximum gradient is set arises because gradients steeper than 15 degree require a range of engineering interventions such as stable foundation systems, advanced stormwater infrastructure, and extensive maintenance regimes. The observed gradient-dependence of the distribution reflects the subtle trade-offs between technical feasibility, economic feasibility, user safety, and accessibility in mountainous infrastructures. This empirical knowledge is crucial for strategic infrastructure planning under resource constraints that aims to maximise the amount of accessibility supply provided. These disparities in space originate from a combination of the engineering difficulties and high construction costs in steep areas, the safety concerns of disabled and elderly users, and simple economic or technological limits to the establishment of accessibility in high-gradient areas. Such a distribution pattern at different altitudes is consistent with the results of previous studies at various analysis scales, and also indicates a deterministic relation in infrastructure development decisions between topography and landscape.
The coverage of the facilities exhibits a consistent spatial decay from the core to the peripheral areas. Zone performance is better with core infrastructure (85% coverage, accessibility score 4.2/5.0, service density 8.3 facilities/km²), making a clear effort to prioritize high utilization areas in infrastructure deployment. The presence of declining rates from 62% in buffer areas to 38% respectively in peripheral settings and subsequently to 15% in remote areas reflects a spatial inequity in the distribution of current services supply. This strong gradient maps into direct distance with the main distribution networks with accessibility scores dropping from 4.2 in core areas down to 1.8 in remote sectors. The observed distribution pattern reflects strategic resource concentration in areas of maximum user density, a response to both practical construction limitations in challenging terrain and economic optimization imperatives.
Table 6 presents comprehensive spatial metrics quantifying barrier-free infrastructure distribution across distinct zones within Huangshan Scenic Area. These metrics reveal pronounced disparities in accessibility provision between core and peripheral sectors. Core tourist zones achieve superior performance with 85% coverage, an accessibility score of 4.2/5.0, and service density of 8.3 facilities/km², demonstrating clear prioritization of high-visitation areas in infrastructure allocation. The systematic decline in coverage rates—from 62% in buffer zones to 38% in peripheral areas and 15% in remote locations—exemplifies the spatial inequity inherent in current service provision patterns. This pronounced gradient correlates directly with distance from primary tourist circuits, as evidenced by accessibility scores diminishing from 4.2 in core zones to 1.8 in remote sectors. The observed distribution pattern reflects strategic resource concentration in areas of maximum visitor density, a response to both practical construction limitations in challenging terrain and economic optimization imperatives. These empirical findings establish a quantitative baseline for assessing distributional equity in barrier-free infrastructure within mountainous tourism destinations contexts, where achieving universal coverage remains constrained by topographical and economic realities.
Digital information infrastructure demonstrates concentrated deployment in primary infrastructure zones, reflecting the strategic importance of user traffic patterns. Comprehensive information support systems cover 73% of primary circulation routes, while remote network segments exhibit substantial coverage gaps. This distribution pattern demonstrates strong spatial autocorrelation (Moran’s I = 0.68), aligning closely with both physical facility distribution and user movement patterns.
Figure 9 presents the spatial analysis of barrier-free infrastructure service density across Huangshan Scenic Area, revealing hierarchical accessibility patterns throughout the mountainous terrain. Kernel density analysis delineates five distinct service levels, with high-density clusters concentrated in topographically favorable zones. These concentration patterns exhibit significant spatial autocorrelation (Moran’s I = 0.68, P < 0.01), confirming systematic rather than random infrastructure distribution. Secondary service zones form concentric buffer areas around primary clusters, establishing a hierarchical network that corresponds with user flow patterns and accessibility requirements. Statistical analysis reveals a significant negative correlation between service density and terrain complexity (r = -0.73, P < 0.01), with infrastructure provision declining markedly in areas characterized by steep gradients and challenging topography. The analysis identifies 2.5 kilometers as a critical service radius threshold, beyond which accessibility diminishes substantially, particularly in peripheral sectors. This spatial distribution pattern demonstrates pronounced inequity in service provision: core infrastructure zones containing 85% of facilities achieve accessibility scores exceeding 4.2, while peripheral regions with only 15% of facilities register scores below 1.8. The strong positive correlation between service density and structural performance (r = 0.82, P < 0.001) within well-serviced zones validates current distribution strategies while simultaneously highlighting service deficits requiring strategic intervention in future infrastructure planning.
Geospatial analysis of the dissemination of barrier-free environment facilities can provide important geographical background information for the comprehensive evaluation of the appropriateness of the site. In this evaluation, qualitative service and spatial distribution patterns are integrated to explore how different functional areas of Huangshan Scenic Area may respond to diverse visitor needs. It emphasizes that a barrier-free infrastructure has to serve multi-faceted accessibility demands – with all of the associated performance and functional requirements its service provision forms an essential element of modern mountain tourism resorts. This spatial-functional synthesis facilitates the identification of specialized zones calibrated to support differentiated user requirements within an overarching accessibility framework.
4.3 Suitability Evaluation Results
It embodies the multiple with the various human-environment relationships comprehensively both about the plants and facilities in Huangshan Scenic Spot Typology Again ease recreational facilities evaluation, such as environmental factors, facilities and infrastructure construction, management and service systems. This is one step further than conventional physical access, which now more productively captures, for example, the harmonisation between barrier-free infrastructure and special operating requirements/the user -centred functional experiences. The integration other certain access facilities with environment enhancing structure arises as a new area of development of mountain works show some references in the near future. The findings of the spatial distribution of suitability score in different functional regions of Huangshan Scenic Area are revealed in Fig. 10. The map shows that there is a strong spatial mismatch of suitability scores and preservation zones have on average the highest overall suitability score (0.85) although the highest number are concentrated in Health Preservation zones, which have both a high level of environmental quality and service provision. The spatial patterns indicate that the best barrier-free suitability emerges at the junction between sites with suitable environmental conditions (moderate elevation and preferred microclimates) and concentration of intervention sites. This distribution confirms that there is an environmental-facility complementary relationship which dominates experiences in visitor use empirically. The delineation of specialized functional zones results from systematic integration of physical, informational, and service accessibility dimensions within the comprehensive evaluation framework.
Figure 11 demonstrates that active recreation areas—zones specifically designed for physical activities and structured exercise programs within natural settings—exhibit consistently strong performance across all evaluation criteria. These zones achieve particularly high scores in infrastructure development (4.3/5.0) and service quality (0.88), reflecting their comprehensive facility provisions. The mild gradients of elevation and the different types of settlement/terrains in these areas provide optimal environments for different rehabilitation programs, both natural therapeutic elements and organized physical activity.
Service-Integrated Zones, merging service networks with natural environment and scored at 88% for environmental quality and 87% for the presence of a strong institutional support system. Spatial analysis shows that the operation of these units is in the critical 2.5 km service zone of base hospitals delivering an immobilisation time due to the mean emergency response of 3.5 min. This nearness can ensure that the patients that need high level medical interventions can come to them, without sacrificing the therapeutic characteristics of natural settings. Table 7 Describes the overall performance metrics for each health tourism zone as well as the performance across all assessment aspects. Health preservation zones rank highest in global suitability (0.85) and environmental quality (DMEP rating = 95%), resource index (0.88) and infrastructure advance (4.5/5.0) and service quality (0.92). These synthetic indicators avail the synergic influence of the environmental attitudes and infrastructures on the optimisation of the conditions for the well-tourism without barriers.
Comparative analysis reveals differentiated performance patterns across zone typologies. Sports and recovery areas exhibit strong multidimensional performance (overall suitability: 0.78), excelling particularly in service quality (0.88) and infrastructure development (4.3/5.0). Medical healing zones display balanced performance characteristics (overall suitability: 0.72), with infrastructure development (4.4/5.0) representing their primary strength. Aged care facilities, despite registering the lowest overall suitability score (0.68), maintain robust infrastructure (4.1/5.0) and service quality (0.83) metrics that align with their specialized geriatric care functions. These performance differentials illustrate how distinctive combinations of environmental, infrastructural, and service components generate functionally specialized zones that accommodate heterogeneous visitor requirements within the comprehensive barrier-free tourism framework.
Analysis of the relationship between infrastructure development and service quality reveals a strong positive correlation (r = 0.82, P < 0.001), with this association being particularly pronounced in health preservation zones. These zones achieve exceptional service quality scores (0.92) supported by superior infrastructure provisions (4.5/5.0), demonstrating how robust physical infrastructure establishes the foundation for enhanced service delivery. This symbiotic relationship manifests throughout the healthcare tourism system, where advanced infrastructure facilitates optimized patient care workflows and enables comprehensive therapeutic program implementation.
Figure 12 illustrates the significant correlation between infrastructure development and environmental quality across all healthcare tourism zones (r = 0.78, P < 0.01). This relationship reaches its apex in health preservation areas, where environmental quality (95%) coincides with the highest infrastructure scores (4.5/5.0). The analysis confirms that optimal service quality emerges from the simultaneous presence of favorable environmental conditions and well-developed infrastructure, as evidenced by the comprehensive metrics presented in Table 7. Aged care facilities—specialized zones configured for geriatric visitors requiring enhanced accessibility support and medical supervision—demonstrate functional adequacy despite lower overall suitability scores (0.68). These facilities maintain high service coverage (80%) and qualified staffing levels (4.1/5.0), indicating effective adaptation to their specialized care requirements.
Figure 12 illustrates the infrastructure-environment relationship across healthcare tourism zones, revealing a strong positive correlation (r = 0.78, P < 0.01) between infrastructure development and environmental quality. Health preservation areas demonstrate optimal performance in both dimensions, positioning at the upper extreme of the distribution. The scatter plot delineates distinct clustering patterns: sports and recovery areas exhibit consistently high performance across both variables, while medical healing and aged care facilities display greater variability in their infrastructure-environment relationships. This visualization empirically validates the zone-specific variations that fundamentally influence barrier-free suitability outcomes.
The correlation coefficients ranging from 0.59 to 0.82 indicate substantial synergies among healthcare tourism components, suggesting opportunities for integrated cluster development that optimizes resource utilization while maintaining service quality. These empirical findings provide a quantitative foundation for strategic planning, identifying specific areas for targeted improvement while leveraging existing infrastructural strengths within the healthcare tourism system.
The analysis demonstrates that service quality optimization requires the simultaneous presence of robust infrastructure and environmental preservation, particularly within health preservation and sports recovery zones. These findings indicate that future development strategies should adopt integrated approaches that enhance service delivery systems while preserving the inherent therapeutic qualities of natural environments. Such holistic planning frameworks ensure sustainable development that balances accessibility enhancement with environmental stewardship.
5. Discussion
The evaluation results generate substantive insights into barrier-free infrastructure provision at Huangshan Scenic Area while elucidating broader dynamics in nature-based infrastructure accessibility. This discussion examines how site-specific findings contribute to understanding global challenges in balancing accessibility, conservation, and sustainability within protected area management frameworks. The analysis situates the Huangshan case within contemporary international discourse on inclusive infrastructure development in environmentally sensitive contexts.
The Huangshan case fundamentally challenges binary conceptualizations of accessibility. The empirical evidence demonstrates that accessibility operates along a continuum shaped by the interplay of environmental, infrastructural, and service dimensions. This finding resonates with mobilities paradigm perspectives that theorize mobility as socially constructed through dynamic interactions among physical infrastructure, regulatory frameworks, and embodied practices [19]. Statistical analysis identifies two pivotal relationships with significant theoretical implications. First, the robust positive correlation between infrastructure development and structural performance (r = 0.82, P < 0.001) empirically substantiates theoretical propositions linking built environment interventions to inclusive tourism outcomes [20]. Second, the significant negative correlation between facility density and terrain gradient (r = -0.73, P < 0.01) delineates critical boundary conditions for accessibility implementation within topographically complex environments.
The findings illuminate nuanced relationships between barrier-free infrastructure development and conservation imperatives. Contrary to dichotomous framings that position accessibility and conservation as inherently conflicting objectives, the Huangshan case exemplifies how thoughtfully designed barrier-free infrastructure can enhance access while maintaining ecological integrity [21]. The spatially differentiated accessibility patterns across functional zones demonstrate how strategic zoning approaches can reconcile competing priorities through context-responsive design interventions. The empirical findings regarding material performance in extreme mountain environments substantiate theoretical propositions linking engineered material selection to long-term infrastructure sustainability, with advanced composite materials demonstrating 40% reduction in maintenance requirements despite initial cost premiums of 40-60% compared to conventional materials, validating life-cycle cost-benefit analyses that prioritize durability over initial capital expenditure in challenging topographical contexts where maintenance access remains severely constrained and environmental exposure accelerates material degradation through freeze-thaw cycling, ultraviolet radiation, and persistent moisture infiltration.
Specialized functional zones exemplify integrated sustainability approaches through their exceptional performance metrics. The superior environmental quality (95%) achieved in environmentally optimized zones, coupled with robust accessibility provisions (4.5/5.0), challenges conventional assumptions regarding inherent trade-offs between access enhancement and conservation. These findings suggest synergistic relationships are achievable within comprehensive sustainability frameworks, transcending traditional dichotomous conceptualizations of operational efficiency versus environmental stewardship in infrastructure service delivery [21].
The findings point out the significant challenges in the development of barrier-free facilities in a heritage site like Huangshan. The site’s unique geomorphological and architectonic features of great cultural significance call for highly sensitive accessibility interventions that consider both the maintenance of historical continuity and the new demands for access. The high positive correlation that was observed between infrastructure and services (r = 0.82, P < 0.001) suggests a complementary relationship between them. Further, the problems involved in ensuring accessibility for hillside terrain reflect the fine balance required in trading off heritage preservation for modernization.
This empirical investigation advances theoretical understanding by establishing explicit linkages between infrastructure quality and environmental performance within specialized facility contexts [22]. While this relationship has been theoretically acknowledged, systematic empirical documentation remains limited in existing literature. The research addresses this gap by providing foundational evidence for developing integrated theoretical frameworks for sustainable facility management. The performance variations observed across facility typologies—environmental quality zones, active recreation areas, integrated service zones, and assisted living facilities—demonstrate that infrastructure-environment relationships are context-dependent [10], thereby adding nuanced complexity to existing theoretical models.
The findings of this research have important implications for policymakers and managers of infrastructure facilities. Strategic investment in specialist infrastructure systems can efficiently enhance service delivery while supporting environmental sustainability [18]. These results inform resource allocation strategies and development planning related to multi-functional facilities, particularly in geographically challenging regions. The Huangshan case demonstrates the imperative of balancing environmental conservation with imperatives of accessibility in infrastructure development in steeply sloping terrains. Barrier-free construction of buildings in environmentally sensitive and culturally significant locations entails site-specific protection measures that ensure heritage conservation while advancing universal accessibility objectives. The determination of key environmental and infrastructural factors enables targeted facility optimization measures.
The evaluative framework developed through the Huangshan case study demonstrates strong transferability value to mountain tourism destinations globally, particularly those sharing similar topographical complexity where slopes exceed 30 degrees, rainfall exceeds 2,000mm annually, and elevation ranges encompass 800-2,000 meters, typical conditions at UNESCO World Heritage mountain tourist sites like Mount Fuji (Japan), Dolomites (Italy), and Rocky Mountain Parks (Canada) [7]. The authors’ threshold of critical 15-degree slope for economically viable barrier-free infrastructure installation as a universal engineering constraint across diverse geographical conditions is supported by comparative studies demonstrating similar points of inflection under alpine conditions in Switzerland (13-17 degrees) and Himalayan foothills (12-16 degrees), suggesting root physics-based constraints irrespective of local construction practices or regulatory frameworks [23,24].
This 3D evaluation framework introduces physical accessibility (0.45 weighting), information accessibility (0.35) and service accessibility (0.20) to allow flexible parameters setting based on destination-specific features; some destination could intensify on service accessibility (since the arrival of infrastructure for ski lift system), and others could be taken into account to pay a higher weight to the information accessibility (also in case of internationalness of pilgrim mount). Strong relationships found between infrastructure development and service quality (r = 0.82) and between terrain gradient and facility density (r = 0.73) are universal functions of gravitational physical factors, material properties under load, and human physiological limits rather than site-specific factors, set quantitative targets for accessibility planning under similar topographical conditions, whether in the Andes or Japanese Alps[23].
Some methodological limitations must be recognized. The cross-sectional design does not allow for definitive causal explanations of the infrastructure-environment-service relationships. Geographic coverage was restricted to one particular destination that may restrict generalizability of the findings to other contexts of mountain tourism destinations. Furthermore, although the quantitative methodology has strong statistical evidence, it may fail to adequately capture qualitative aspects of users’ experiences and environmental effects in niche infrastructure facilities.[17].
The validated assessment methodology generates opportunities for comparative application across diverse mountain tourism contexts, with particular relevance to sites experiencing similar convergence of high visitation pressure (>3 million annual visitors), extreme topographical constraints (gradients >35 degrees), and heritage conservation mandates that collectively necessitate innovative engineering solutions balancing accessibility enhancement with environmental preservation[25]. The critical inquiries will be: how techno-morphological responses and intelligent designs minimize environmental consequences and maximize accessibility in terrains with natural inclinations in heritage with complex topography. This encompasses investigating new technologies like responsive materials and modular design system that can adapt to both conservation and accessibility needs respectively. Longitudinal studies may offer insights to the longer term influences of these innovative solutions on user access outcomes and heritage preserving indicators, and evidence of empirical nature for the long term plan strategies.
Future research should prioritize the integration of smart design technologies within heritage-sensitive environments. Critical inquiries will relate to the extent of adaptive infrastructure and smart design systems that can successfully mitigate environmental impacts and improve access in topographically challenging heritage contexts. This involves investigation into new technologies responsive materials and modular design systems that can dynamically respond to accommodating conservation imperatives and accessibility needs. Longitudinal monitoring might measure the lasting effects of these creative solutions on user accessibility results and heritage conservation markers, serving as an evidence to inform long-term preservation strategies.
6. Conclusions
This study contributes to the knowledge of accessible infrastructure development in mountainous tourism regions with a systematic assessment of Huangshan Scenic Area. The results illustrate that systems that provide effective infrastructure free from barriers must incorporate both physical, informational and operational accessibility in models that are also sensitive to conservation and sustainability demands. The case from Huangshan offers empirical evidence of the possibility of synergizing accessibility improvement and heritage preservation, a crucial approach to sustainable development of mountain infrastructure. The constructed evaluation index system constitutes a methodological framework for the evaluation of barrier-free infrastructure systematically including complex topographical, ecological and cultural dimensions typical of mountainous regions and has proven general applicability for destinations with similar features of intense gradients (>30 degrees), high precipitation (>2,000mm annually), and significant elevation variations (>1,000m), providing quantitative instruments for the planning of infrastructural measures transferable to mountainous tourism destinations ranging from the European Alps to the Andes that face similar engineering challenges and require evidence-based assessment methodologies.
Through identification of spatial-functional relationships between facility distribution and user requirements, this research extends theoretical understanding of accessibility infrastructure in topographically challenging contexts. The robust correlation between infrastructure development and service quality (r = 0.82, P < 0.001) underscores the necessity of integrated approaches encompassing both physical and operational dimensions. From a practical perspective, the research provides actionable tools for mountain infrastructure projects navigating the balance between accessibility provision and resource conservation. The three-dimensional assessment framework offers evidence-based methodologies for strategic decision-making, while the identified differential performance patterns across functional zones inform intervention prioritization in resource-constrained settings. Future research should pursue comparative analyses across diverse mountain infrastructure sites to elucidate contextual factors shaping barrier-free implementation. Investigation of how emerging digital technologies can augment physical infrastructure presents additional research opportunities. These technological innovations offer potential pathways for enhancing accessibility while preserving the ecological integrity of sensitive mountain environments. “The technical specifications validated through this research, including material performance thresholds (freeze-thaw resistance >100 cycles, friction coefficients >0.6), structural load factors (2.5-3.0 for slopes >30°), and the critical 15° gradient inflection point, provide immediate operational guidance for infrastructure projects in comparable mountainous environments. These quantified parameters enable evidence-based decision-making in project planning, budgeting, and implementation phases, ultimately advancing the development of inclusive tourism infrastructure in topographically challenging destinations worldwide.
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Table 1: Global Barrier-free Infrastructure development Indicators
Table 2. Data sources and specifications
Table 3. Hierarchical structure of the barrier-free infrastructure evaluation index system
Table 4. Classification of barrier-free infrastructure evaluation results
Table 5. Weights of evaluation indicators for barrier-free infrastructure
Table 6. Spatial Distribution Metrics of Barrier-free infrastructure
Table 7: Comprehensive Evaluation Metrics for Specialized Infrastructure Zones
Table S1. Comprehensive Spatial Analysis Results for Barrier-free infrastructure in Huangshan Scenic Area
Figure 1: Conceptual Framework of Mountainous tourism destinations Accessibility Development
Figure 2. Location of the study area.
Figure 3. Structure of the barrier-free infrastructure evaluation model
Figure 4. Multi-level Framework for Barrier-free Infrastructure Evaluation: Weighted Indicators and Dimensional Structure in Mountainous tourism destinations Context
Figure 5. Spatial analysis and distribution framework of barrier-free infrastructure in Huangshan Scenic area
Figure 6. Hot Spot Analysis of Barrier-free Infrastructure Distribution in Huangshan Scenic Area Based on Terrain Analysis
Figure 7. Spatial Analysis of Slope Gradient-Facility Density Relationship in Huangshan Scenic Area (2023-2024)
Figure 8. Distribution and corresponding accessibility score of barrier-free infrastructure in Huangshan Scenic area
Figure 9. Spatial Analysis of Barrier-free Infrastructure Service Density Distribution in Huangshan Scenic Area
Figure 10. Spatial Distribution of Barrier-free infrastructure and Accessibility Scores
Figure 11. Comparative Analysis of Multi-criterion Performance Metrics Across Healthcare Tourism Zones
Figure 12: Infrastructure-Environment Relationship Analysis
Table 1: Global Barrier-free Infrastructure development Indicators
| Dimension | Current Status | Future Potential |
| Market Size | $150 billion globally | Projected to reach $200 billion by 2025 |
| Accessibility Rate | 35% of facilities | Target of 80% by 2030 |
| User Satisfaction | 45% satisfaction rate | Expected 75% with improvements |
| Economic Impact | 12% of tourism GDP | Potential growth to 18% |
Table 2. Data sources and specifications
| Data Category | Data Type | Source | Time Range |
| Environmental Data | Temperature, precipitation, humidity | Huangshan Meteorological Bureau | 2013-2023 |
| Air quality index, noise levels | Huangshan Environmental Protection Bureau | 2020-2024 | |
| Water quality data | Huangshan Water Resources Bureau | 2021-2024 | |
| Spatial Data | DEM (30m resolution) | Resource and Environment Science and Data Center | 2023 |
| Land use/cover maps | Huangshan Natural Resources Bureau | 2023 | |
| Administrative boundaries | Anhui Geographic Information Center | 2023 | |
| Infrastructure Data | Tourist facilities location | Huangshan Tourism Administration | 2023 |
| Transportation networks | Huangshan Transportation Bureau | 2023 | |
| Barrier-free infrastructure inventory | Field survey | 2023-2024 | |
| Tourism Statistics | Visitor flow data | Huangshan Infrastructure development Committee | 2019-2024 |
| Tourist satisfaction surveys | Huangshan Tourism Research Institute | 2022-2024 |
Table 3. Hierarchical structure of the barrier-free infrastructure evaluation index system
| Primary Dimension | Secondary Indicators | Tertiary Indicators | Weight |
| Physical Accessibility (0.45) | Path System (0.20) | Gradient compliance | 0.08 |
| Surface stability | 0.07 | ||
| Width adequacy | 0.05 | ||
| Rest Facilities (0.15) | Distribution density | 0.06 | |
| Shelter provision | 0.05 | ||
| Seating ergonomics | 0.04 | ||
| Emergency Access (0.10) | Evacuation routes | 0.04 | |
| Medical access points | 0.03 | ||
| Equipment storage | 0.03 | ||
| Information Accessibility (0.35) | Wayfinding (0.15) | Signage visibility | 0.06 |
| Tactile guidance | 0.05 | ||
| Audio assistance | 0.04 | ||
| Digital Support (0.12) | Mobile coverage | 0.04 | |
| App accessibility | 0.04 | ||
| Real-time updates | 0.04 | ||
| Service Accessibility (0.20) | Human Assistance (0.10) | Staff availability | 0.04 |
| Training quality | 0.03 | ||
| Language support | 0.03 |
Table 4. Classification of barrier-free infrastructure evaluation results
| Suitability Level | Score Range | Characteristics | Recommended Actions |
| Highly Suitable | 0.8-1.0 | Complete facilities, excellent accessibility | Maintain current standards |
| Suitable | 0.6-0.8 | Good facilities, minor improvements needed | Targeted enhancements |
| Moderately Suitable | 0.4-0.6 | Basic facilities present, significant gaps | Systematic upgrades |
| Marginally Suitable | 0.2-0.4 | Limited facilities, major deficiencies | Comprehensive renovation |
| Unsuitable | 0.0-0.2 | Inadequate or absent facilities | Complete redesign |
Table 5. Weights of evaluation indicators for barrier-free infrastructure
| Category | Indicator | Local Weight | Global Weight | CR Value |
| Infrastructure Accessibility | Path gradient | 0.285 | 0.092 | 0.068 |
| Surface material | 0.242 | 0.078 | 0.072 | |
| Width adequacy | 0.473 | 0.153 | 0.065 | |
| Facility Configuration | Rest areas | 0.388 | 0.089 | 0.073 |
| Sanitary facilities | 0.342 | 0.079 | 0.070 | |
| Signage system | 0.270 | 0.062 | 0.075 | |
| Safety Measures | Emergency exits | 0.412 | 0.095 | 0.069 |
| Warning systems | 0.328 | 0.076 | 0.071 | |
| First-aid stations | 0.260 | 0.060 | 0.074 |
Table 6. Spatial Distribution Metrics of Barrier-free infrastructure
| Spatial Dimension | Coverage Rate | Accessibility Score | Service Density |
| Core Tourist Zone | 85% | 4.2/5.0 | 8.3 facilities/km² |
| Buffer Zone | 62% | 3.8/5.0 | 5.1 facilities/km² |
| Peripheral Area | 38% | 2.9/5.0 | 2.7 facilities/km² |
| Remote Locations | 15% | 1.8/5.0 | 0.9 facilities/km² |
Table 7: Comprehensive Evaluation Metrics for Specialized Infrastructure Zones
| Zone Type | Environmental Quality | Resource Index | Infrastructure Score | Service Quality | Overall Suitability |
| Environmental Quality Zone | 95% | 0.88 | 4.5/5.0 | 0.92 | 0.85 |
| Active Recreation Zone | 92% | 0.75 | 4.3/5.0 | 0.88 | 0.78 |
| Integrated Service Zone | 88% | 0.70 | 4.4/5.0 | 0.85 | 0.72 |
| Assisted Living Zone | 85% | 0.65 | 4.1/5.0 | 0.83 | 0.68 |
Table S1. Comprehensive Spatial Analysis Results for Barrier-free infrastructure in Huangshan Scenic Area
| Parameter Category | Metric | Value | Statistical Significance |
| Hot Spot Analysis | Moran’s I (Global) | 0.47 | p < 0.01 |
| Hot Spots (99% confidence) | 23 facilities | Z-score > 2.58 | |
| Hot Spots (95% confidence) | 18 facilities | Z-score 1.96-2.58 | |
| Hot Spots (90% confidence) | 12 facilities | Z-score 1.65-1.96 | |
| Cold Spots (99% confidence) | 19 facilities | Z-score < -2.58 | |
| Cold Spots (95% confidence) | 14 facilities | Z-score -2.58 to -1.96 | |
| Cold Spots (90% confidence) | 8 facilities | Z-score -1.96 to -1.65 | |
| Service Density Analysis | Level 1 (Highest Density) | 614,590.7501 – 768,238.4375 points/km² | n/a |
| Level 2 (High Density) | 460,943.0626 – 614,590.7500 points/km² | n/a | |
| Level 3 (Moderate Density) | 307,295.3751 – 460,943.0625 points/km² | n/a | |
| Level 4 (Low Density) | 153,647.6876 – 307,295.3750 points/km² | n/a | |
| Level 5 (Lowest Density) | 0 – 153,647.6875 points/km² | n/a | |
| Spatial Autocorrelation (Moran’s I) | 0.68 | p < 0.01 | |
| Service Density-Terrain Correlation | -0.73 | p < 0.01 | |
| Service Density-Structural performance Correlation | 0.82 | p < 0.001 | |
| Critical Service Radius Threshold | 2.5 km | n/a | |
| Slope-Facility Relationship | Low Gradient Zone (0-15°) Coverage | >95% | n/a |
| Low Gradient Zone Facility Density | 8.3 facilities/km² | n/a | |
| Intermediate Gradient Zone (15-45°) Coverage Range | 62% to 38% | n/a | |
| Intermediate Gradient Zone Cost Increase | 40-60% per 10° slope increase | n/a | |
| High Gradient Zone (>45°) Coverage | <20% | n/a | |
| High Gradient Zone Facility Density | 0.9 facilities/km² | n/a | |
| High Gradient Zone Cost Increase | >200% above baseline | n/a | |
| Critical Slope Inflection Point | 15° | n/a | |
| Slope-Facility Density Correlation | -0.73 | p < 0.01 | |
| Zonal Statistics | Core Tourist Zone Coverage | 85% | n/a |
| Core Tourist Zone Accessibility Score | 4.2/5.0 | n/a | |
| Core Tourist Zone Facility Density | 8.3 facilities/km² | n/a | |
| Buffer Zone Coverage | 62% | n/a | |
| Buffer Zone Accessibility Score | 3.8/5.0 | n/a | |
| Buffer Zone Facility Density | 5.1 facilities/km² | n/a | |
| Peripheral Area Coverage | 38% | n/a | |
| Peripheral Area Accessibility Score | 2.9/5.0 | n/a | |
| Peripheral Area Facility Density | 2.7 facilities/km² | n/a | |
| Remote Location Coverage | 15% | n/a | |
| Remote Location Accessibility Score | 1.8/5.0 | n/a | |
| Remote Location Facility Density | 0.9 facilities/km² | n/a | |
| Information Accessibility | Primary Tourist Routes Coverage | 73% | n/a |
| Secondary Trail Digital Coverage | 42% | n/a | |
| Remote Trail Digital Coverage | 18% | n/a | |
| Information-Facility Correlation | 0.68 | p < 0.01 |
Note: This supplementary table provides comprehensive quantitative results from spatial analysis of barrier-free infrastructure in Huangshan Scenic Area, complementing the condensed presentation in the main text. Points/km² refers to service points per square kilometer as calculated through kernel density estimation. Statistical significance is indicated where applicable, with n/a denoting metrics where statistical significance testing was not applicable.
Figure 1: Conceptual Framework of Mountainous tourism destinations Accessibility Development
Figure 2. Location of the study area.
Figure 3. Structure of the barrier-free infrastructure evaluation model
Figure 4. Multi-level Framework for Barrier-free Infrastructure Evaluation: Weighted Indicators and Dimensional Structure in Mountainous tourism destinations Context
Note: Schematic representation of the three-tier evaluation framework showing primary dimensions (physical, information, and service accessibility), secondary indicators, and tertiary metrics with corresponding weights (N=27 indicators). Weights derived from ANP-Delphi expert consultation (n=28 experts, Kendall’s W=0.82).
Figure 5. Spatial analysis and distribution framework of barrier-free infrastructure in Huangshan Scenic area
Figure 6. Hot Spot Analysis of Barrier-free infrastructure Distribution in Huangshan Scenic Area Based on Terrain Analysis
Note: Spatial distribution analyzed using Getis-Ord Gi* statistic (Moran’s I = 0.47, P < 0.01) with confidence levels shown for hot spots (red) and cold spots (blue) across the terrain gradient. Analysis based on GPS-verified locations of 127 barrier-free infrastructure overlaid on digital elevation model (DEM). Scale bar indicates 5 km distance interval.
Figure 7. Spatial Analysis of Slope Gradient-Facility Density Relationship in Huangshan Scenic Area (2023-2024)
Note: Quantitative relationship between terrain slope (degrees) and barrier-free infrastructure density (%). Blue dots represent individual measurement points (n = 127); red line indicates linear regression trend (r = -0.73, P < 0.01). Note the critical threshold at 15° slope where facility density begins significant decline. Shaded areas represent 95% confidence intervals. Density measurements normalized to facilities per square kilometer. Analysis conducted using ArcGIS 10.5 with facility locations verified through GPS ground-truthing (±0.25m accuracy). Slope data derived from 30m DEM. Statistical significance determined using Monte Carlo simulation (999 permutations).
Source: Field survey data collected from Huangshan Tourism Administration (March 2023-February 2024). Spatial analysis performed using ArcGIS 10.5. Statistical significance verified through Monte Carlo simulation (999 permutations). GPS data accuracy: ±0.25m, n = 127 facilities.
Figure 8. Distribution and corresponding accessibility score of barrier-free infrastructure in Huangshan Scenic area
Note: Choropleth map showing spatial variation in barrier-free infrastructure distribution (n=127) and corresponding accessibility scores. Color gradient represents accessibility index values (range 1.8-4.2). Inset graphs display zonal statistics for core, buffer, and peripheral areas. Spatial autocorrelation coefficient (Moran’s I = 0.68) indicates significant clustering patterns.
Source: Field survey data collected from Huangshan Tourism Administration (March 2023-February 2024). Spatial analysis performed using ArcGIS 10.5. Statistical significance verified through Monte Carlo simulation (999 permutations). GPS data accuracy: ±0.25m, n = 127 facilities.
Figure 9. Spatial Analysis of Barrier-free Infrastructure Service Density Distribution in Huangshan Scenic Area
Note: Service density analysis overlaid on terrain model showing density clusters (measured in service points per square kilometer) with corresponding accessibility levels. Black dots represent individual service points. Analysis based on kernel density estimation with 2.5km service radius threshold.
Figure 10. Spatial Distribution of Barrier-free infrastructure and Accessibility Scores
Figure 11. Comparative Analysis of Multi-criterion Performance Metrics Across Healthcare Tourism Zones
Figure 12: Infrastructure-Environment Relationship Analysis